Finding experiments

To use incense we first have to instantiate an experiment loader that will enable us to query the database for specific runs.

targets_type iteration autoencoder_type batch_size artifacts
exp_id
17 Mnist False Over_dim_iteration 256 {'history_autoencoder_iteration': Artifact(nam...
18 Mnist False Over_dim_iteration 128 {'history_autoencoder_iteration': Artifact(nam...
19 Mnist False Over_dim_iteration 64 {'history_autoencoder_iteration': Artifact(nam...
20 Mnist False Over_dim_iteration 32 {'history_autoencoder_iteration': Artifact(nam...
21 10_Targets False Over_dim_iteration 256 {'history_autoencoder_iteration': Artifact(nam...
22 10_Targets False Over_dim_iteration 128 {'history_autoencoder_iteration': Artifact(nam...
23 10_Targets False Over_dim_iteration 64 {'history_autoencoder_iteration': Artifact(nam...
24 10_Targets False Over_dim_iteration 32 {'history_autoencoder_iteration': Artifact(nam...
74 Noisy False Over_dim_iteration 256 {'history_autoencoder': Artifact(name=history_...
75 Noisy False Over_dim_iteration 128 {'history_autoencoder': Artifact(name=history_...
targets_type iteration autoencoder_type batch_size artifacts sort
exp_id
21 10_Targets False Over_dim_iteration 256 {'history_autoencoder_iteration': Artifact(nam... 0
22 10_Targets False Over_dim_iteration 128 {'history_autoencoder_iteration': Artifact(nam... 1
23 10_Targets False Over_dim_iteration 64 {'history_autoencoder_iteration': Artifact(nam... 2
24 10_Targets False Over_dim_iteration 32 {'history_autoencoder_iteration': Artifact(nam... 3
17 Mnist False Over_dim_iteration 256 {'history_autoencoder_iteration': Artifact(nam... 4
18 Mnist False Over_dim_iteration 128 {'history_autoencoder_iteration': Artifact(nam... 5
19 Mnist False Over_dim_iteration 64 {'history_autoencoder_iteration': Artifact(nam... 6
20 Mnist False Over_dim_iteration 32 {'history_autoencoder_iteration': Artifact(nam... 7
74 Noisy False Over_dim_iteration 256 {'history_autoencoder': Artifact(name=history_... 8
75 Noisy False Over_dim_iteration 128 {'history_autoencoder': Artifact(name=history_... 9

Red best overall, and also best of subset. Bes means for accuracy max, rest min. Green best of subset.

predictions_df_0
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.9848 0.9817 0.9757 0.9638 0.977 0.9759 0.9747 0.9725 0.9717 0.9703
1 0.9818 0.9763 0.9305 0.9384 0.9721 0.9695 0.9698 0.9654 0.9606 0.959
2 0.9817 0.9762 0.9162 0.9333 0.9604 0.9547 0.9525 0.9452 0.941 0.941
3 0.9817 0.9762 0.9065 0.9332 0.9427 0.937 0.9251 0.922 0.9195 0.9193
4 0.9817 0.9762 0.8987 0.9326 0.9193 0.9117 0.8902 0.8862 0.8965 0.8954
5 0.9817 0.9762 0.8731 0.9326 0.8922 0.8785 0.8458 0.8433 0.8709 0.8718
6 0.9817 0.9762 0.8701 0.9326 0.8575 0.8433 0.8019 0.7862 0.8476 0.8499
7 0.9817 0.9762 0.8701 0.9326 0.8167 0.8049 0.7578 0.7337 0.8256 0.8236
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.403742 0.397198 0.382812 0.388587 0.0292309 0.0339636 0.0360619 0.0344924 0.652874 0.653378
1 0.407135 0.405824 0.394443 0.400576 0.0463176 0.0545498 0.0602712 0.0584108 0.669197 0.670428
2 0.407422 0.40694 0.399517 0.405517 0.0675954 0.0800329 0.0893665 0.0863392 0.685468 0.687311
3 0.407448 0.407088 0.402149 0.407292 0.0904182 0.106922 0.119572 0.115036 0.70102 0.703296
4 0.407449 0.407112 0.404266 0.408127 0.113555 0.13365 0.149717 0.14319 0.715709 0.718164
5 0.407449 0.407114 0.407281 0.408358 0.136202 0.159653 0.178439 0.169983 0.729506 0.73188
6 0.407449 0.407115 0.40784 0.408404 0.158043 0.184622 0.206047 0.195145 0.742406 0.74451
7 0.407449 0.407115 0.407942 0.408414 0.178906 0.208454 0.232604 0.218491 0.754443 0.756112
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.265401 0.264138 0.26606 0.259944 0.0513701 0.0553199 0.0564859 0.0551706 0.378762 0.376407
1 0.265915 0.265573 0.267783 0.261732 0.0653205 0.0713066 0.0747933 0.0734418 0.389247 0.38766
2 0.265972 0.265772 0.269007 0.262598 0.0805217 0.0888189 0.0941929 0.092148 0.399146 0.398025
3 0.265977 0.265805 0.269806 0.262848 0.0953927 0.105831 0.112724 0.109869 0.408407 0.407519
4 0.265977 0.265811 0.270858 0.262942 0.109518 0.121862 0.1302 0.126343 0.416992 0.41614
5 0.265977 0.265811 0.271821 0.262971 0.122724 0.136864 0.146277 0.141473 0.424931 0.423939
6 0.265977 0.265811 0.27194 0.262975 0.135043 0.150866 0.161319 0.155292 0.432269 0.43101
7 0.265977 0.265811 0.271963 0.262974 0.146518 0.163961 0.175466 0.167862 0.439067 0.437445 
predictions_df_10
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.9799 0.9763 0.9709 0.9589 0.9673 0.9672 0.9677 0.9618 0.9672 0.9668
1 0.9752 0.9711 0.9269 0.9348 0.9665 0.962 0.9618 0.9527 0.958 0.9564
2 0.9753 0.9708 0.9123 0.9297 0.9529 0.9477 0.9435 0.9359 0.9387 0.9382
3 0.9753 0.9708 0.9033 0.9286 0.933 0.928 0.9161 0.903 0.9138 0.9181
4 0.9753 0.9708 0.8932 0.9281 0.9095 0.9014 0.8793 0.863 0.8928 0.8955
5 0.9753 0.9708 0.872 0.9282 0.8784 0.8677 0.8331 0.8146 0.8702 0.8715
6 0.9753 0.9708 0.87 0.9282 0.8423 0.8292 0.7933 0.762 0.8482 0.8481
7 0.9753 0.9708 0.87 0.9282 0.8002 0.7843 0.7468 0.7097 0.825 0.8221
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.402999 0.395499 0.377159 0.385465 0.0399669 0.0433849 0.0458721 0.0470132 0.653984 0.654814
1 0.407379 0.405662 0.390463 0.399108 0.0549084 0.0616757 0.0677522 0.068914 0.67046 0.671816
2 0.407784 0.407174 0.396012 0.404569 0.0749327 0.0858256 0.0954971 0.0961543 0.686544 0.688534
3 0.407801 0.407408 0.398971 0.406481 0.0968927 0.11186 0.124867 0.124517 0.701879 0.70437
4 0.407802 0.407438 0.401572 0.407466 0.119405 0.137996 0.153959 0.152344 0.716393 0.71908
5 0.407802 0.407442 0.404292 0.407803 0.141745 0.163562 0.182658 0.178932 0.730049 0.732646
6 0.407802 0.407442 0.404807 0.407867 0.163358 0.188274 0.20948 0.203792 0.742828 0.745155
7 0.407802 0.407442 0.404918 0.407878 0.184035 0.212257 0.235622 0.226996 0.754794 0.756653
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.26548 0.264068 0.264819 0.259829 0.0614194 0.0638013 0.0651297 0.0661549 0.381173 0.378757
1 0.266103 0.265653 0.266559 0.261613 0.0721238 0.07678 0.080333 0.0811993 0.390269 0.38877
2 0.266171 0.265939 0.267765 0.26247 0.0857087 0.0928656 0.0982885 0.0986782 0.399767 0.398799
3 0.266174 0.265985 0.268615 0.262705 0.0996325 0.109077 0.11606 0.115747 0.40883 0.408122
4 0.266174 0.265992 0.269689 0.262814 0.113161 0.124596 0.132863 0.131755 0.417292 0.416612
5 0.266174 0.265993 0.270502 0.262856 0.126055 0.139256 0.148822 0.14653 0.425143 0.42431
6 0.266174 0.265993 0.270614 0.262864 0.138164 0.153065 0.163409 0.16003 0.432417 0.431306
7 0.266174 0.265993 0.270639 0.262864 0.149485 0.16618 0.177339 0.172386 0.439173 0.437674 
predictions_df_20
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.9704 0.9683 0.9636 0.9526 0.9535 0.9545 0.9511 0.9423 0.9629 0.9607
1 0.9678 0.9638 0.9194 0.9285 0.9526 0.9538 0.9493 0.9403 0.9538 0.9523
2 0.9672 0.9638 0.9021 0.9215 0.9392 0.9355 0.9288 0.917 0.9351 0.9346
3 0.9671 0.9638 0.8946 0.9214 0.9185 0.9119 0.8972 0.8785 0.9135 0.9154
4 0.9671 0.9638 0.8856 0.92 0.8889 0.8804 0.8544 0.8346 0.8905 0.8926
5 0.9671 0.9638 0.8645 0.9197 0.8556 0.8436 0.8122 0.7825 0.8681 0.8676
6 0.9671 0.9638 0.8633 0.9196 0.8192 0.8077 0.7613 0.7232 0.8454 0.845
7 0.9671 0.9638 0.8633 0.9195 0.7772 0.77 0.7202 0.671 0.8223 0.8206
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.402029 0.393151 0.370475 0.382019 0.0519608 0.0546186 0.0576784 0.0621365 0.655572 0.656806
1 0.407717 0.405333 0.386412 0.397403 0.0652168 0.0709145 0.0776066 0.0823035 0.67222 0.67365
2 0.408289 0.407198 0.393006 0.40362 0.0842901 0.093695 0.104295 0.108502 0.688173 0.69007
3 0.40835 0.407518 0.396174 0.405981 0.105636 0.118774 0.132812 0.136141 0.703368 0.705605
4 0.408351 0.407564 0.399054 0.40727 0.127556 0.144172 0.161267 0.163401 0.717735 0.720078
5 0.408352 0.407569 0.401673 0.407816 0.149179 0.16899 0.189259 0.189331 0.73123 0.733484
6 0.408352 0.40757 0.402246 0.407986 0.170097 0.192987 0.215755 0.213773 0.743865 0.745872
7 0.408352 0.40757 0.402362 0.408047 0.190324 0.215841 0.240812 0.236253 0.755651 0.757263
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.265637 0.264096 0.263457 0.260027 0.0713328 0.0730259 0.0746911 0.0780058 0.38401 0.381504
1 0.266365 0.265695 0.265606 0.261874 0.079737 0.0835761 0.0874313 0.0905882 0.391674 0.390139
2 0.266469 0.266017 0.266919 0.262805 0.0920443 0.0981407 0.104103 0.106644 0.400779 0.399711
3 0.266481 0.266073 0.267723 0.263115 0.105174 0.113417 0.121031 0.122825 0.409636 0.408784
4 0.266481 0.266081 0.268802 0.263275 0.118098 0.128306 0.137274 0.138208 0.417954 0.417117
5 0.266481 0.266083 0.269537 0.26337 0.13043 0.142441 0.152709 0.152433 0.425696 0.424716
6 0.266481 0.266083 0.269655 0.263402 0.14205 0.155778 0.167047 0.165544 0.432875 0.431643
7 0.266481 0.266083 0.269682 0.263408 0.153052 0.16824 0.180358 0.177393 0.439517 0.437949 
predictions_df_30
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.9579 0.9569 0.9517 0.9421 0.9299 0.9327 0.9291 0.9143 0.956 0.9528
1 0.954 0.9516 0.9041 0.9111 0.9329 0.9319 0.9247 0.9081 0.9452 0.9478
2 0.953 0.951 0.8884 0.903 0.9189 0.9154 0.9027 0.8784 0.925 0.9291
3 0.953 0.9509 0.8802 0.9022 0.8932 0.8906 0.8675 0.8391 0.9015 0.9075
4 0.953 0.9509 0.8725 0.9008 0.8608 0.8601 0.8268 0.7913 0.8819 0.8834
5 0.953 0.9509 0.8567 0.9001 0.8246 0.8234 0.7813 0.7329 0.8593 0.8623
6 0.953 0.9509 0.856 0.8998 0.7857 0.7852 0.7346 0.6782 0.8399 0.8372
7 0.953 0.9509 0.856 0.8997 0.7448 0.7466 0.6889 0.6239 0.8193 0.8112
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.40201 0.391454 0.365024 0.378182 0.0655538 0.067508 0.0716126 0.0861135 0.657567 0.659072
1 0.409904 0.406427 0.382609 0.395726 0.0772725 0.0819139 0.0897807 0.105963 0.674399 0.675981
2 0.410503 0.408983 0.390059 0.403515 0.0952452 0.103297 0.115343 0.131461 0.690095 0.692167
3 0.410528 0.409377 0.394017 0.406829 0.115633 0.1273 0.143244 0.158357 0.705024 0.707504
4 0.410529 0.409432 0.397393 0.40863 0.136808 0.15209 0.171209 0.185038 0.719212 0.721859
5 0.410529 0.409446 0.399795 0.409405 0.157707 0.176353 0.198546 0.210386 0.732596 0.735132
6 0.410529 0.409451 0.400378 0.40972 0.178159 0.199896 0.225659 0.233841 0.745156 0.747396
7 0.410529 0.409451 0.400521 0.409867 0.197545 0.22272 0.249986 0.255627 0.756881 0.758684
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.266435 0.26473 0.263247 0.260379 0.081913 0.0829286 0.0851656 0.0940992 0.38735 0.384617
1 0.267615 0.266616 0.265379 0.262522 0.0883726 0.0913939 0.0958708 0.105251 0.393387 0.391876
2 0.267711 0.267033 0.266672 0.263688 0.0992905 0.104545 0.111273 0.120127 0.401957 0.40098
3 0.267712 0.267098 0.267532 0.264126 0.111414 0.118854 0.127536 0.135363 0.410548 0.409816
4 0.267712 0.267106 0.268595 0.264334 0.123636 0.13317 0.143293 0.150039 0.41871 0.418011
5 0.267712 0.267108 0.269206 0.264453 0.135414 0.146832 0.158284 0.163657 0.426357 0.425513
6 0.267712 0.26711 0.269328 0.264512 0.146658 0.159833 0.172749 0.176066 0.43348 0.432357
7 0.267712 0.26711 0.269362 0.264536 0.157131 0.172197 0.185608 0.187455 0.440098 0.43861 
predictions_df_40
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.9286 0.9355 0.9319 0.9194 0.8924 0.894 0.8934 0.8694 0.9451 0.9428
1 0.9299 0.9305 0.8811 0.8928 0.9001 0.8988 0.8909 0.8598 0.9357 0.9389
2 0.9297 0.9296 0.866 0.885 0.8852 0.8789 0.8614 0.8248 0.9181 0.9224
3 0.9297 0.9295 0.8588 0.8827 0.8645 0.8512 0.8273 0.781 0.8958 0.8992
4 0.9297 0.9295 0.8504 0.8814 0.8315 0.8191 0.7885 0.7259 0.8724 0.8779
5 0.9297 0.9295 0.839 0.881 0.7944 0.7837 0.7375 0.6743 0.852 0.857
6 0.9297 0.9295 0.8387 0.8805 0.7593 0.7463 0.6957 0.6251 0.8295 0.8321
7 0.9297 0.9295 0.8387 0.8802 0.7201 0.7038 0.6565 0.5677 0.8066 0.8122
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.402065 0.38873 0.359412 0.374456 0.0817783 0.0835792 0.0893766 0.120947 0.659909 0.66194
1 0.412575 0.40705 0.37987 0.394187 0.0922067 0.0964227 0.105899 0.139457 0.677104 0.678895
2 0.413643 0.410571 0.388267 0.403303 0.109051 0.116376 0.130318 0.164275 0.692663 0.694841
3 0.413706 0.411189 0.392883 0.407578 0.128452 0.139374 0.157354 0.190461 0.707296 0.709866
4 0.413709 0.411278 0.396449 0.409941 0.14864 0.162956 0.184909 0.216084 0.721191 0.723912
5 0.413709 0.411286 0.398828 0.411019 0.168841 0.18653 0.211371 0.240408 0.734347 0.736905
6 0.413709 0.411287 0.399568 0.41146 0.188507 0.209535 0.236577 0.262834 0.746753 0.748851
7 0.413709 0.411287 0.399744 0.411684 0.207486 0.231597 0.260627 0.283335 0.758428 0.759857
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.267698 0.2654 0.263535 0.261213 0.0936516 0.0945045 0.0975511 0.115138 0.391233 0.388439
1 0.269343 0.267494 0.266027 0.263642 0.0985905 0.101272 0.106443 0.124693 0.395577 0.39409
2 0.269529 0.268031 0.267292 0.265106 0.108289 0.112985 0.120652 0.138465 0.40355 0.402624
3 0.269541 0.268144 0.268174 0.265706 0.119491 0.126324 0.136036 0.152765 0.411798 0.411111
4 0.269541 0.268163 0.269114 0.265978 0.130904 0.139738 0.151265 0.166493 0.419726 0.419061
5 0.269541 0.268165 0.26965 0.266136 0.14206 0.152851 0.165599 0.179334 0.427212 0.426369
6 0.269541 0.268165 0.269798 0.266211 0.152735 0.165392 0.179029 0.191051 0.43424 0.433049
7 0.269541 0.268165 0.269839 0.266262 0.162852 0.177259 0.191638 0.201624 0.440815 0.439154 
predictions_df_50
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.8886 0.9013 0.9005 0.8932 0.8549 0.8501 0.8444 0.8171 0.9279 0.9278
1 0.8915 0.8953 0.8522 0.8645 0.8648 0.8543 0.8376 0.8072 0.9243 0.9259
2 0.8913 0.8943 0.8376 0.8566 0.8499 0.8368 0.8098 0.7747 0.9035 0.9085
3 0.8914 0.8943 0.8309 0.8536 0.8228 0.8072 0.7694 0.7298 0.8828 0.8835
4 0.8914 0.8943 0.8238 0.852 0.7888 0.7755 0.729 0.6744 0.8596 0.8615
5 0.8914 0.8943 0.8153 0.8507 0.7538 0.7393 0.6881 0.6199 0.8395 0.8399
6 0.8914 0.8943 0.8152 0.8499 0.7172 0.7041 0.6466 0.5676 0.8195 0.8192
7 0.8914 0.8943 0.8152 0.8492 0.682 0.6651 0.6064 0.5218 0.8002 0.7965
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.404547 0.388145 0.355368 0.371496 0.0996954 0.101952 0.119126 0.189564 0.663194 0.665695
1 0.41807 0.409956 0.377992 0.394078 0.108782 0.113559 0.135789 0.208704 0.680711 0.68282
2 0.419471 0.414477 0.387368 0.404558 0.124522 0.132098 0.159161 0.232202 0.696009 0.698491
3 0.41956 0.415359 0.392621 0.409467 0.142962 0.153597 0.185206 0.256812 0.710305 0.713272
4 0.419562 0.415513 0.396436 0.412502 0.162224 0.176127 0.211652 0.280807 0.72382 0.727139
5 0.419563 0.415532 0.398942 0.413933 0.181475 0.198786 0.237343 0.30346 0.73659 0.740001
6 0.419563 0.415534 0.399799 0.414552 0.200372 0.221268 0.261529 0.325053 0.748646 0.751882
7 0.419563 0.415534 0.400022 0.414947 0.218378 0.242679 0.284769 0.344019 0.760004 0.762828
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.270287 0.267307 0.264952 0.262616 0.105995 0.106965 0.116014 0.15242 0.395963 0.392933
1 0.272464 0.269693 0.26781 0.265496 0.109453 0.112477 0.124262 0.16141 0.398502 0.397029
2 0.272731 0.270321 0.26911 0.26725 0.117968 0.122914 0.137297 0.173835 0.405758 0.404942
3 0.272748 0.27049 0.270018 0.267933 0.128202 0.135055 0.151782 0.186901 0.413574 0.413105
4 0.272748 0.270521 0.270856 0.268319 0.138832 0.147622 0.16623 0.199509 0.421178 0.420852
5 0.272748 0.270525 0.271387 0.268548 0.149291 0.160042 0.179969 0.211271 0.428384 0.428036
6 0.272748 0.270526 0.271556 0.268671 0.159375 0.172172 0.192712 0.22232 0.435167 0.434638
7 0.272748 0.270526 0.271602 0.26875 0.16885 0.183579 0.204782 0.23195 0.441542 0.440678 
predictions_df_60
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.8367 0.8472 0.8507 0.8458 0.7888 0.794 0.7829 0.7457 0.9058 0.8999
1 0.8419 0.843 0.8051 0.8192 0.8047 0.8026 0.7804 0.7281 0.906 0.9073
2 0.8409 0.842 0.7912 0.8099 0.789 0.7823 0.7521 0.6908 0.8842 0.8892
3 0.8409 0.8423 0.7851 0.8053 0.7639 0.7565 0.7156 0.6464 0.8646 0.8668
4 0.8409 0.8425 0.7796 0.8033 0.7331 0.7215 0.6796 0.5922 0.8415 0.8456
5 0.8409 0.8425 0.7742 0.8027 0.7024 0.6839 0.6355 0.5464 0.8213 0.821
6 0.8409 0.8425 0.7741 0.8025 0.6649 0.648 0.5966 0.5043 0.7976 0.801
7 0.8409 0.8425 0.7741 0.8024 0.6308 0.6129 0.5557 0.4634 0.7778 0.7792
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.40765 0.388622 0.351771 0.369919 0.122039 0.126166 0.165388 0.287639 0.667369 0.670564
1 0.427041 0.41591 0.377085 0.395794 0.129919 0.136762 0.181192 0.306055 0.685583 0.6882
2 0.428843 0.422289 0.387553 0.408811 0.144255 0.153891 0.203111 0.328218 0.700852 0.703803
3 0.429025 0.423586 0.393211 0.415273 0.161309 0.173901 0.227722 0.351252 0.714941 0.718307
4 0.429031 0.423821 0.397461 0.419155 0.179454 0.195076 0.252844 0.373813 0.728282 0.731806
5 0.429031 0.423847 0.400114 0.420831 0.197445 0.216456 0.277437 0.395017 0.740881 0.744291
6 0.429031 0.42385 0.401098 0.42137 0.215076 0.23751 0.300842 0.414595 0.752775 0.755853
7 0.429031 0.42385 0.401378 0.421584 0.231962 0.257941 0.323384 0.432573 0.763976 0.766536
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.274055 0.270886 0.267108 0.265315 0.120676 0.122518 0.142482 0.204069 0.401584 0.39843
1 0.277572 0.273914 0.270653 0.269 0.122883 0.12688 0.149657 0.212075 0.402309 0.400985
2 0.277939 0.274881 0.272176 0.271311 0.130116 0.135986 0.161371 0.22324 0.408879 0.40826
3 0.277975 0.275122 0.273005 0.272308 0.139208 0.146944 0.174702 0.235059 0.416326 0.416002
4 0.277977 0.275169 0.273759 0.272818 0.148924 0.158515 0.188184 0.24656 0.423688 0.42342
5 0.277977 0.275175 0.274236 0.273043 0.158484 0.170084 0.201158 0.257293 0.430716 0.430317
6 0.277977 0.275175 0.274419 0.273099 0.167742 0.181332 0.213374 0.267149 0.437372 0.436694
7 0.277977 0.275175 0.27447 0.27311 0.176523 0.192131 0.22502 0.276159 0.443644 0.44256 
predictions_df_70
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.7681 0.7736 0.7863 0.7806 0.7172 0.7169 0.7033 0.6482 0.8749 0.8705
1 0.7754 0.7804 0.7457 0.7644 0.7308 0.7211 0.6959 0.6232 0.8796 0.8755
2 0.7746 0.7801 0.7312 0.7571 0.7155 0.7056 0.6686 0.5829 0.8574 0.8577
3 0.7746 0.7799 0.7275 0.7552 0.6947 0.6786 0.63 0.5398 0.8394 0.8358
4 0.7746 0.7799 0.7234 0.7525 0.6638 0.6502 0.5933 0.4903 0.8166 0.8153
5 0.7746 0.7799 0.7185 0.7515 0.6263 0.62 0.5587 0.45 0.7958 0.7966
6 0.7746 0.7799 0.7185 0.751 0.5949 0.5852 0.5281 0.4147 0.7792 0.7746
7 0.7746 0.7799 0.7187 0.7509 0.5646 0.5555 0.4964 0.3856 0.761 0.756
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.410797 0.390256 0.348375 0.368509 0.148181 0.153608 0.246155 0.466543 0.673333 0.676965
1 0.436226 0.423234 0.376743 0.396726 0.154913 0.163683 0.261233 0.484374 0.692575 0.695464
2 0.439251 0.43193 0.388703 0.412208 0.168067 0.17997 0.281876 0.504546 0.70782 0.710971
3 0.439418 0.433716 0.394774 0.419637 0.183648 0.198585 0.305455 0.525229 0.721559 0.725026
4 0.439422 0.43396 0.39943 0.42405 0.200329 0.218863 0.328992 0.545226 0.734477 0.73804
5 0.439423 0.433981 0.402412 0.425877 0.217076 0.238997 0.352158 0.564188 0.746643 0.750072
6 0.439423 0.433983 0.403699 0.426478 0.233655 0.259041 0.374713 0.581057 0.75809 0.761163
7 0.439423 0.433983 0.404121 0.426724 0.249807 0.278494 0.396594 0.596849 0.768821 0.771363
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.278267 0.274983 0.270121 0.268238 0.137213 0.139711 0.185964 0.295296 0.408737 0.40524
1 0.283003 0.2789 0.274463 0.272121 0.138302 0.143327 0.192304 0.302461 0.407669 0.406275
2 0.283638 0.280318 0.276318 0.274772 0.144398 0.151475 0.202942 0.312104 0.413383 0.412764
3 0.283676 0.280669 0.277108 0.275847 0.152326 0.161286 0.215362 0.322313 0.420254 0.419943
4 0.283677 0.280715 0.277881 0.276384 0.160975 0.172052 0.227747 0.33223 0.427182 0.426934
5 0.283677 0.28072 0.278367 0.276644 0.169683 0.182742 0.239806 0.341618 0.433857 0.433492
6 0.283677 0.28072 0.278595 0.27675 0.178264 0.193292 0.251437 0.349923 0.440175 0.439547
7 0.283677 0.28072 0.278676 0.276784 0.186555 0.20345 0.262574 0.35766 0.446124 0.445117 
predictions_df_80
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.676 0.6844 0.6944 0.6818 0.6367 0.6278 0.597 0.5299 0.8292 0.8287
1 0.6906 0.702 0.6648 0.6822 0.6451 0.629 0.599 0.5033 0.8314 0.8318
2 0.6908 0.7024 0.6556 0.68 0.6381 0.6111 0.575 0.4774 0.8159 0.8185
3 0.6907 0.7023 0.6531 0.6788 0.6206 0.5896 0.5382 0.4376 0.7965 0.7996
4 0.6907 0.7023 0.6507 0.6777 0.5888 0.5672 0.5092 0.3987 0.7792 0.778
5 0.6907 0.7023 0.6488 0.6774 0.5636 0.5368 0.4805 0.3643 0.7614 0.7583
6 0.6907 0.7023 0.6489 0.6765 0.539 0.5088 0.4554 0.3327 0.7416 0.7388
7 0.6907 0.7023 0.6489 0.6763 0.5089 0.4844 0.4256 0.3109 0.7239 0.7203
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.417814 0.393367 0.348816 0.370509 0.18009 0.188496 0.384405 0.773584 0.681764 0.686335
1 0.450517 0.433106 0.379292 0.401461 0.185615 0.198562 0.399041 0.79183 0.702655 0.70583
2 0.454228 0.443733 0.392422 0.418621 0.197017 0.213236 0.417627 0.80865 0.718311 0.721202
3 0.454544 0.445724 0.398698 0.42669 0.210987 0.230243 0.438798 0.825761 0.731824 0.734809
4 0.454552 0.445979 0.403285 0.431569 0.225775 0.248417 0.460401 0.842244 0.744445 0.747266
5 0.454552 0.446002 0.40654 0.433399 0.240855 0.267129 0.481661 0.857966 0.756367 0.758691
6 0.454552 0.446004 0.408108 0.433915 0.255625 0.285987 0.50176 0.872566 0.767566 0.769196
7 0.454552 0.446004 0.408649 0.434149 0.270112 0.304591 0.521461 0.886265 0.778067 0.77888
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.284672 0.280654 0.275078 0.272587 0.156653 0.160321 0.257476 0.448744 0.417861 0.414172
1 0.291017 0.285196 0.280224 0.276573 0.156628 0.163584 0.26326 0.455895 0.41516 0.413564
2 0.291834 0.286853 0.282653 0.279414 0.161386 0.170532 0.27246 0.463481 0.420138 0.419119
3 0.29191 0.287241 0.283586 0.280512 0.168068 0.17918 0.283355 0.471558 0.426499 0.42563
4 0.291912 0.287294 0.284215 0.281066 0.175408 0.188597 0.29452 0.479468 0.433032 0.432078
5 0.291912 0.287299 0.284681 0.281299 0.182981 0.1983 0.30543 0.487048 0.439405 0.438171
6 0.291912 0.2873 0.284943 0.28138 0.190422 0.208022 0.315679 0.494089 0.445487 0.443825
7 0.291912 0.2873 0.285054 0.281429 0.197676 0.217566 0.325619 0.500684 0.451232 0.449058 
predictions_df_90
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.5741 0.5789 0.5924 0.5796 0.5376 0.5347 0.4992 0.4003 0.7381 0.7441
1 0.5912 0.6028 0.5694 0.5992 0.5512 0.5361 0.4989 0.3624 0.7545 0.7551
2 0.5932 0.6035 0.5638 0.603 0.5427 0.5239 0.4792 0.3388 0.7427 0.7464
3 0.5929 0.6035 0.5609 0.602 0.5243 0.5034 0.4553 0.3155 0.7249 0.7335
4 0.5929 0.6035 0.5588 0.5998 0.505 0.4853 0.4297 0.2941 0.7071 0.7146
5 0.5929 0.6035 0.5579 0.5989 0.4796 0.4677 0.4046 0.2688 0.6858 0.6973
6 0.5929 0.6035 0.558 0.5982 0.457 0.4453 0.3859 0.2502 0.671 0.6789
7 0.5929 0.6035 0.558 0.5982 0.4383 0.4249 0.371 0.2352 0.6556 0.6638
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.425812 0.398201 0.350201 0.372566 0.220935 0.245757 0.649353 1.31741 0.693606 0.699147
1 0.464508 0.443792 0.382918 0.404827 0.22597 0.256416 0.664977 1.33298 0.716716 0.720447
2 0.468334 0.457096 0.397021 0.423436 0.236609 0.269858 0.681133 1.34565 0.733068 0.736146
3 0.468613 0.459656 0.403164 0.432388 0.249656 0.285689 0.698919 1.35867 0.746445 0.749317
4 0.468633 0.459996 0.407728 0.438209 0.263084 0.302162 0.717598 1.37166 0.758506 0.761129
5 0.468634 0.460029 0.411233 0.44049 0.276701 0.318654 0.736029 1.38326 0.769638 0.771899
6 0.468635 0.460031 0.413078 0.441093 0.290003 0.336094 0.753106 1.39419 0.78003 0.781762
7 0.468635 0.460032 0.413717 0.441347 0.302931 0.353041 0.769905 1.40523 0.789749 0.790846
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.291348 0.286751 0.280529 0.276974 0.180427 0.191823 0.390611 0.717463 0.429491 0.425428
1 0.298661 0.292086 0.28653 0.280939 0.179755 0.195017 0.39666 0.723347 0.425312 0.4236
2 0.299456 0.294244 0.289442 0.283862 0.183718 0.201023 0.404397 0.728795 0.429423 0.42837
3 0.299516 0.294775 0.290429 0.285069 0.189605 0.208751 0.413308 0.734735 0.435124 0.434172
4 0.299517 0.294854 0.291068 0.285694 0.195975 0.217013 0.422738 0.740791 0.441048 0.439984
5 0.299517 0.294862 0.291598 0.28603 0.202559 0.225404 0.432033 0.746235 0.446843 0.445533
6 0.299517 0.294862 0.291927 0.286137 0.209033 0.234247 0.440638 0.751377 0.452389 0.450725
7 0.299517 0.294862 0.292042 0.286178 0.215344 0.242821 0.449046 0.756612 0.457632 0.455547 
predictions_df_100
Accuracy over iterations evaluations_feature_classifier
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.4823 0.4839 0.4906 0.4733 0.4349 0.4429 0.3895 0.2745 0.6428 0.6443
1 0.4973 0.515 0.4706 0.5043 0.4428 0.4409 0.3792 0.233 0.6565 0.6557
2 0.4975 0.5168 0.4664 0.5121 0.4357 0.424 0.3651 0.2179 0.6453 0.6528
3 0.4976 0.517 0.466 0.5138 0.4229 0.4052 0.3492 0.2083 0.6272 0.6373
4 0.4976 0.517 0.4641 0.511 0.4059 0.3892 0.3304 0.1957 0.6177 0.6229
5 0.4976 0.517 0.4635 0.5105 0.3908 0.3789 0.3162 0.1853 0.6026 0.6093
6 0.4976 0.517 0.4635 0.5104 0.3731 0.363 0.3051 0.1753 0.586 0.5968
7 0.4976 0.517 0.4635 0.5103 0.3583 0.3488 0.2947 0.1648 0.5751 0.5868
Loss over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.436829 0.407245 0.356266 0.379787 0.280696 0.341972 1.09486 2.00171 0.710982 0.717736
1 0.482005 0.458285 0.391727 0.414688 0.286548 0.356475 1.11107 2.01262 0.737424 0.741281
2 0.486998 0.473787 0.406676 0.435306 0.295102 0.370187 1.12433 2.01951 0.754701 0.757179
3 0.487398 0.476682 0.412737 0.445237 0.305669 0.385362 1.13925 2.02665 0.767848 0.769833
4 0.487408 0.477064 0.417276 0.451614 0.317304 0.40188 1.15463 2.03374 0.779417 0.780985
5 0.487408 0.477116 0.420977 0.454004 0.328882 0.418724 1.16897 2.04073 0.78999 0.791073
6 0.487408 0.477123 0.422943 0.454522 0.340263 0.434641 1.18278 2.04709 0.79973 0.800222
7 0.487408 0.477123 0.423602 0.454657 0.351226 0.451215 1.19685 2.05348 0.808793 0.808585
MAE over iterations autoencoder
Over_dim_iteration 256 10_Targets Over_dim_iteration 128 10_Targets Over_dim_iteration 64 10_Targets Over_dim_iteration 32 10_Targets Over_dim_iteration 256 Mnist Over_dim_iteration 128 Mnist Over_dim_iteration 64 Mnist Over_dim_iteration 32 Mnist Over_dim_iteration 256 Noisy Over_dim_iteration 128 Noisy
0 0.299818 0.294712 0.28758 0.283684 0.213528 0.242457 0.611274 1.05384 0.444565 0.440164
1 0.308448 0.30089 0.294478 0.288183 0.212619 0.247261 0.617602 1.0578 0.43963 0.437413
2 0.309511 0.303408 0.297675 0.291512 0.215195 0.253088 0.623779 1.06051 0.443046 0.441268
3 0.309608 0.303962 0.298687 0.292871 0.219559 0.260254 0.631147 1.06358 0.448056 0.446258
4 0.30961 0.304037 0.299357 0.29356 0.2248 0.268253 0.63882 1.06677 0.453358 0.451387
5 0.30961 0.304048 0.299932 0.293908 0.230128 0.27652 0.645998 1.06996 0.45858 0.45633
6 0.30961 0.304049 0.300279 0.293984 0.235426 0.284405 0.652874 1.0729 0.46359 0.460975
7 0.30961 0.30405 0.300412 0.293997 0.24055 0.292587 0.659833 1.07587 0.468375 0.465303